Microstructure characterization and maximization of the material removal rate in nano-powder mixed EDM of Al-Mg 2 Si metal matrix composite—ANFIS and RSM approaches

  • Mehdi Hourmand*
  • , Ahmed A.D. Sarhan
  • , Saeed Farahany
  • , Mohd Sayuti
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

Al-Mg 2 Si in situ composite is a new metal matrix composite (MMC) with numerous applications in different engineering fields. MMCs are considered difficult-to-cut materials due to the abrasive nature of the reinforcement (e.g., Mg 2 Si), hardness, and built-up edge. Hence, electrical discharge machining (EDM) is one of the alternative ways to machine Al-Mg 2 Si. With EDM, it is possible to machine conductive materials with different strength, temperature resistance, and hardness as well as produce complicated shapes, high-aspect ratio slots, and deep cavities with precise dimensions and good surface finish. The experiments in this study were designed by response surface methodology (RSM) and ANFIS was utilized to analyze the nano-powder mixed EDM (NPMEDM) of Al-Mg 2 Si in situ composite. The study represents the impacts of NPMEDM parameters on changes in microstructure and material removal rate (MRR). The results revealed that among all interactions, the current-voltage and current-pulse ON time interactions have the most significant effect on MRR. Moreover, current has most significant effect, followed by voltage, pulse ON time and duty factor. An analysis of the Al-Mg 2 Si microstructure demonstrated that current, pulse ON time, and voltage have remarkable impact on the microstructure, size of craters, and profile of the machined surface. Moreover, decrease in spark energy leads to less microstructural change and better surface finish.

Original languageEnglish
Pages (from-to)2723-2737
Number of pages15
JournalInternational Journal of Advanced Manufacturing Technology
Volume101
Issue number9-12
DOIs
StatePublished - 19 Apr 2019

Bibliographical note

Publisher Copyright:
© 2018, Springer-Verlag London Ltd., part of Springer Nature.

Keywords

  • Adaptive neuro-fuzzy inference system (ANFIS)
  • Al-Mg Si metal matrix composite (MMC)
  • Material removal rate (MRR)
  • Microstructure
  • Nano-powder mixed electrical discharge machining (Nano-powder mixed EDM)
  • Response surface methodology (RSM)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Fingerprint

Dive into the research topics of 'Microstructure characterization and maximization of the material removal rate in nano-powder mixed EDM of Al-Mg 2 Si metal matrix composite—ANFIS and RSM approaches'. Together they form a unique fingerprint.

Cite this